A Systematic Review and Meta-Analysis Examining Pneumonia-Associated Mortality in Dementia
Bibliographic record
Abstract
BACKGROUND: Although it is generally accepted that deaths associated with pneumonia are more common in patients with dementia, no comprehensive reviews on the subject have previously been published. SUMMARY: Relevant studies were identified through a literature search of the PubMed, EMBASE, Scopus, and ISI Web of Science databases for publications up to August 2013. Studies were included if (1) a group of adult subjects with dementia and a (comparison) group composed of subjects without dementia were included, (2) the cause(s) of death was/were reported, and (3) pneumonia was identified as one of the possible causes of death. The occurrence of death due to pneumonia associated with dementia was expressed as an odds ratio (OR) with 95% confidence interval (CI). Thirteen studies were included. The odds of death resulting from pneumonia were significantly increased for persons with any form of dementia compared with those without dementia (OR = 2.22, 95% CI 1.44-3.42, p < 0.001). In a subgroup analysis, using the results from 8 studies that restricted inclusion to persons with Alzheimer's disease, the odds of death resulting from pneumonia were also significantly higher (OR = 1.70, 95% CI 1.12-2.58, p = 0.013). Key Messages: The odds of pneumonia-associated mortality were increased more than 2-fold for patients with dementia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".